End-to-End Workflows for Coupled
Climate and Hydrological Modeling
Edwin Sumargo (University of Illinois at Urbana-Champaign)
Sylvia Murphy (NOAA/CIRES)
Kathy Saint (SGI Inc)
Outline
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Ongoing Project Objective
System Description
Project Phases
Internship Goals
CAM to SWAT Conversion
Downscaling
Soil and Water Assessment Tool (SWAT)
Remaining Tasks
Summary
Ongoing Project Objective
The development of an end-to-end workflow that executes, in a
loosely coupled mode, a distributed modeling system comprised of
an atmospheric model (CAM) using ESMF and a hydrological model
(SWAT) using OpenMI.
System Description
• SWAT (hydrology model) runs on PC
Personal Computer
• CAM (atmospheric model) runs on HPC
Driver
• Wrappers for both SWAT and CAM
provide OpenMI interface to each model
• Driver (OpenMI Configuration Editor)
uses OpenMI interface to timestep
through models via wrappers
• Access to CAM across the
network provided by ESMF
Web Services
• CAM output data written to
NetCDF files and streamed
to CAM wrapper via ESMF
Web Services
• Resulting output files archived
to science gateway
OpenMI
SWAT
CAM OpenMI
Wrapper
ESMF Web
Services
ESMF CAM
Component
High Performance Computer
Data Files
Project Phases
Phase 1: SWAT & the ESMF stub atmospheric
component communicate via an external netCDF
file (Jan-Mar 2010)
Phase 2: CAM replaces the ESMF atmospheric stub
but both still communicate via the netCDF (Apr-May)
Phase 3: Data flows via socket interfaces with
realistic unit conversions (May-June)
Phase 4: Full streaming on public systems. Data
archived to a science portal (Sept-Oct)
Internship Goals
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Determine the variable and unit conversions necessary to couple
CAM to SWAT
Investigate downscaling methods and determine under which
conditions to use each
Investigate C/C++ nearest neighbor algorithms
Install SWAT on a public PC at NOAA
Investigate SWAT configuration options
Create graphics of SWAT output
Begin the calibration process for SWAT
CAM to SWAT Conversion
• SWAT reference: (Neitsch et al., 2004)
• CAM reference: (McCaa et al., 2004)
Variables needed to be converted:
1. Air Temperature
2. Solar Radiation
3. Precipitation
4. Relative Humidity
5. Wind Speed
Downscaling
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Downscaling methods were investigated
(Fowler et al., 2007)
A method needed to be determined for
both the current and future system
“Downscaling climate data is a strategy
for generating locally relevant data from
Global Circulation Models (GCMs). The
overarching strategy is to connect global
scale predictions and regional dynamics
to generate regionally specific forecasts”
(http://www.climate-decisions.org).
3 fundamental downscaling methods:
– Dynamical Downscaling (DD)
– Statistical Downscaling (SD)
– Nearest Neighbor Interpolation (NNI):
the simplest case
Source: www.southwestclimatechange.org
Dynamical Downscaling
• A downscaling method where a higher resolution climate model is
embedded within a GCM (Fowler et al., 2007).
– Uses regional climate or limited-area models
– Typically resolved at approximately 0.5° latitude and
longitude scale and parameterize physical atmospheric
processes.
• Advantages:
– Performs better at regions where topographic effects are
prominent
– Superior for which convective precipitation is involved
• Disadvantages:
– Computationally very intensive
– Strongly depends on GCM boundary forcing
– Has limited number of scenario ensembles available
Statistical Downscaling
• A downscaling method that establishes empirical relationships
between GCM-resolution climate variables and local climate
(Fowler et al., 2007).
• Advantages:
– More efficient than dynamical downscaling
– More suitable in handling the extremes, e.g. of temperature
– Performs better at higher altitude, mainly with continental
climate
• Disadvantages:
– Underestimates variance
– Excludes climate feedbacks
– Skill is affected by domain size, climatic region, and
season
Nearest Neighbor
Interpolation
• Nearest Neighbor Interpolation was determined to
be the most appropriate downscaling method for
the current system.
– This is because there is only one atmospheric
grid point in the hydrological domain.
– Nearest neighbor interpolation calculates the
distance between the points on the grid and the
center of the hydrological domain.
– We adapted this calculation to the sphere using
the Haversine formula (http://www.movabletype.co.uk/scripts/latlong.html).
• A future phase of the system will involve more than
one atmospheric grid point per hydrological
domain.
– It is anticipated that statistical downscaling will
be used.
SWAT
• SWAT is a river basin scale model developed to quantify the
impact of land management practices in large, complex
watersheds (http://swatmodel.tamu.edu).
– Runs on Windows platform
– Configuration of SWAT is easier with GIS software
– MWSwat is a free GIS interface to SWAT
swat2005 Application
Setup file (file.cio)
GIS with MWSwat
Setup and Run
• Domain: Lake Fork Creek watershed near Quitman, TX
– Default test basin on SWAT2005
• Setup and ran 20-year simulation (1990-2009)
• SWAT outputs data as ASCII texts
• Developed plots of the output
1990-2009 Annual Average Flow
Average Flow (m3/s)
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Observed
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Simulated
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Calibrated
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10
5
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
0
Lake Fork Creek watershed near Quitman, TX
Year
Calibration
• Each SWAT basin must be
calibrated, including the Lake Fork
test basin that comes with SWAT.
• Downloaded the observed time
series from USGS website
– Data are daily mean water
discharges (ft3/s) at Lake Fork
Creek watershed
• Reviewed calibration techniques
• Attempted modification of input
parameters
• Reran to calibrate
• Recalibrated (as needed)
USGS record
Example of calibration slideshow
Remaining Tasks
• Work on MWSwat to configure the output files of SWAT
• Continue SWAT calibration
Summary
To couple an atmospheric model and a hydrological model,
careful unit conversions are needed to connect data flows. To
determine the best downscaling method for the project also
required thorough investigation. Running and calibrating SWAT
were crucial to complete Phase 4 of an end-to-end workflow.
Questions
Earth System Curator: http://earthsystemcurator.org
ESMF: http://earthsystemmodeling.org
OpenMI: http://www.openmi.org
CAM: http://www.ccsm.ucar.edu/models/ccsm4.0/cam
SWAT: http://swatmodel.tamu.edu
MWSwat: http://www.waterbase.org/download_mwswat.html
sumargo1@illinois.edu
sylvia.murphy@noaa.gov
ksaint@sgi.com
Reference: Fowler, H., Blenkinsop, S., & Tebaldi, C. (2007). Linking climate change
modelling to impacts studies. International Journal of Climatology, 27,
1547-1578.